An estimation algorithm for AR models with closely located lightly damped low frequency poles

We present a pole estimation algorithm which is based on an overdetermined adaptive IIR filter with an additional postprocessing stage to extract the pole locations from the adaptive weights. The adaptive filtering algorithm used, is a pseudo-linear regression algorithm which is solved by a time-rec...

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Veröffentlicht in:1997 IEEE International Conference on Acoustics, Speech, and Signal Processing Jg. 5; S. 3821 - 3824 vol.5
Hauptverfasser: Harteneck, M., Stewart, R.W., McWhirter, J.G., Proudler, I.K.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Washington DC IEEE 1997
IEEE Computer Society Press
Schlagworte:
Adaptive filters
Applied sciences
Array signal processing
Brain modeling
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Filtering algorithms
Frequency estimation
IIR filters
Information, signal and communications theory
Polynomials
Predictive models
Sensor arrays
Signal and communications theory
Signal processing algorithms
Signal, noise
Telecommunications and information theory
Infinite impulse response filter
Autoregressive model
Adaptive filter
Signal estimation
ISBN:0818679190, 9780818679193
ISSN:1520-6149
Online-Zugang:Volltext
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Zusammenfassung:We present a pole estimation algorithm which is based on an overdetermined adaptive IIR filter with an additional postprocessing stage to extract the pole locations from the adaptive weights. The adaptive filtering algorithm used, is a pseudo-linear regression algorithm which is solved by a time-recursive QR decomposition. Two pole classification schemes are presented to separate the true poles and the superfluous poles. The classification schemes are based on the occurrence of pole-zero cancelation and on the pole movement in the z-plane. Floating point simulations are presented to demonstrate the performance of the proposed algorithm.
ISBN:0818679190
9780818679193
ISSN:1520-6149
DOI:10.1109/ICASSP.1997.604713